Xiaodi Wu | QuICS

Associate Professor

xwu@cs.umd.edu

3247 Atlantic Building

I am an Associate Professor in the Department of Computer Science and Institute for Advanced Computer Studies at the University of Maryland, College Park, and a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). I am also an Amazon Visiting Academic working for AWS Braket. I am a recipient of the Sloan Research Fellowship, NSF CAREER, and AFOSR YIP awards.

Before coming to Maryland, I was an Assistant Professor in the Computer and Information Science Department at the University of Oregon from 2015 to 2017. Before that, I was a Postdoctoral Associate at Massachusetts Institute of Technology from 2013 to 2015 (advisor: Aram Harrow, Scott Aaronson). I was also a Simons Research Fellow at the Simons Institute for the Theory of Computing at Berkeley, for the program of Quantum Hamiltonian Complexity in Spring 2014. I also spent two summers at the Institute for Quantum Computing, University of Waterloo as a student intern (advisor: John Watrous). I received my Ph.D. in theoretical computer science in 2013 (advisor: Yaoyun Shi) from the University of Michigan, Ann Arbor. I received my B.S. degree in mathematics and physics in 2008 from the Academic Talent Program, Tsinghua University.

My research aims to bridge the gap between the theoretical foundation of quantum computing and the limitation of realistic quantum machines. More specifically, I am working on the foundations of practical quantum applications on realistic quantum machines by investigating computational models that capture the native programmability of quantum devices. I am also building efficient and reliable systems to operate both near-term and long-term quantum devices. Please check my research overview for details of my existing and ongoing projects.

Courses

Advanced Topics in Theory of Computing; The Foundation of End-to-End Quantum Applications (CMSC858O, Spring 2024)

Introduction to Quantum Computing (CMSC457/PHYS457, Fall 2023)

Introduction to Quantum Computing (CMSC457/PHYS457, Spring 2023)

The Foundation of End-to-End Quantum Applications (CMSC858O, Fall 2022)

Introduction to Quantum Computing (CMSC457/PHYS457, Spring 2022)

Publications

2020

K. - M. Chung, Lee, Y., Lin, H. - H., and Wu, X., “Constant-round Blind Classical Verification of Quantum Sampling”, 2020.

S. Chakrabarti, Childs, A. M., Li, T., and Wu, X., “Quantum algorithms and lower bounds for convex optimization”, Quantum, vol. 4, no. 221, 2020.

T. Li, Wang, C., Chakrabarti, S., and Wu, X., “Sublinear classical and quantum algorithms for general matrix games”, To appear in the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), 2020.

2019

S. Chakrabarti, Huang, Y., Li, T., Feizi, S., and Wu, X., “Quantum Wasserstein Generative Adversarial Networks”, Advances in Neural Information Processing Systems (NIPS), vol. 32, 2019.

T. Li and Wu, X., “Quantum query complexity of entropy estimation”, IEEE Transactions on Information Theory, vol. 65, no. 5, pp. 2899-2921, 2019.

K. Hietala, Rand, R., Hung, S. - H., Wu, X., and Hicks, M., “Verified Optimization in a Quantum Intermediate Representation”, 2019.

T. Li, Chakrabarti, S., and Wu, X., “Sublinear quantum algorithms for training linear and kernel-based classifiers”, Proceedings of the 36th International Conference on Machine Learning (ICML 2019) PMLR , vol. 97, pp. 3815-3824, 2019.

A. W. Harrow, Natarajan, A., and Wu, X., “Limitations of semidefinite programs for separable states and entangled games”, Commun. Math. Phys., vol. 366, no. 2, 2019.

2018

S. - H. Hung, Hietala, K., Zhu, S., Ying, M., Hicks, M., and Wu, X., “Quantitative Robustness Analysis of Quantum Programs (Extended Version)”, Proc. ACM Program. Lang., vol. 3, no. POPL, p. Article 31, 2018.

F. G. S. L. Brandão, Kalev, A., Li, T., Lin, C. Yen- Yu, Svore, K. M., and Wu, X., “Quantum SDP Solvers: Large Speed-ups, Optimality, and Applications to Quantum Learning”, To appear at the 46th International Colloquium on Automata, Languages and Programming (ICALP 2019), 2018.

2017

F. G. S. L. Brandão, Kalev, A., Li, T., Lin, C. Yen- Yu, Svore, K. M., and Wu, X., “Exponential Quantum Speed-ups for Semidefinite Programming with Applications to Quantum Learning”, 2017.

Y. - H. Chen, Chung, K. - M., Lai, C. - Y., Vadhan, S. P., and Wu, X., “Computational Notions of Quantum Min-Entropy”, 2017.

X. Wu, Yao, P., and Yuen, H., “Raz-McKenzie simulation with the inner product gadget”, Electronic Colloquium on Computational Complexity (ECCC), 2017.